Searching for Local Solutions: Making Welfare Policy on the Ground in Ontario
Bibliographic record
Abstract
Over recent decades welfare dependency has played a powerful role in defining the welfare “problem” and in passing appropriate “solutions.” One result has been the proliferation of short-term, low-cost employment programs and training programs that have emerged as critical sites for challenging and reforming the attitudes and behaviors of welfare recipients. By exploring work-readiness programs in four communities in Ontario, Canada, we provide insight into how these programs relate to the lived realities of those compelled to attend them. The research shows how dependency discourse informs program rules and content, raising expectations about both the benefits and the immediacy of work. This focus risks individualizing blame and ignoring the structural realities of labor markets and the systemic forces that create poverty and unemployment. Although the particular empirical focus is on Ontario, the approaches used and their outcomes resonate with strategies that are evident wherever neoliberalism has made its mark.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".